Animal Welfare

Animal welfare can be defined as the biological and psychological state of an animal as it attempts to cope with its environment (Broom, 1986). In this definition, welfare includes both pleasurable and unpleasant mental states such as contentment, anxiety, and fear (Fraser and Duncan, 1998). The predominant method of measuring animal welfare focuses on overt physical ailments, such as skin lesions, lameness, and body condition. The evaluation of emotions in animals can be deduced from physiological indicators (e.g. heart rate, glucocorticoid levels, hypothalamic-pituitary-adrenal (HPA) and sympathetic-adrenal-medullary (SAM) activity). Interpretation of these measurements is confounded by the fact that these metrics could reflect an emotion of both positive and negative valence. For example, an increase in heart rate or HPA and SAM activity all indicate high arousal, but can be associated with escape from predation (negative valence) and with anticipation of reward (positive valence).

Cognitive Bias Testing
An alternative metric for assessing the affective state of animals could be the cognitive or judgment bias task. Cognitive bias testing allows researchers to infer how an individual’s emotional state influences information processing, such as the evaluation of ambiguous stimuli (Mendl et al., 2009). This cognitive experiment theorizes that an animal will “judge” or appraise an ambiguous stimulus as predicting either positive or negative outcome depending on the affective state of the animal. This appraisal of stimuli can be the result of mental checks (e.g., dangerous? familiar?) and memory recall, or they can be relatively simple, rapid and automatic reactions (Grandjean and Scherer, 2008).

Research on human and non-human animals indicates that negative mental states, such as anxiety or depression, can induce pessimistic judgments of ambiguous stimuli (Hallion and Ruscio, 2011). For example, barren or unpredictable housing conditions can elicit negative affect states in rats and piglets (Mendl et al., 2009; Douglas et al., 2012).

Cognitive bias assessment

For cognitive bias experiments, operant conditioning methods are used to train animals to distinguish between two stimuli that lie at the ends of a continuous stimulus range.  One stimulus may be associated with a highly valued reward while the other is associated with a lower valued reward or punishment.  The conditioned behavioral response can be locomotion-based, such as approach, or computer-based method, such as touchscreen responses (i.e., peck, nose, press).  Once animals are trained to respond to a positive stimulus (“go”) and to not respond when presented the negative stimulus (“no-go”), their cognitive bias can be explored through the presentation of an ambiguous or intermediate stimulus.  Animals can be classified as “optimistic” or having a positive affective state if the animal displays behaviors that suggest an increased expectation of reward in the face of ambiguous stimuli.  Alternatively, animals can be classified “pessimistic” or having a negative affective state if the animal displays behaviors that suggest an increased expectation of punishment in the face of ambiguous stimuli.


Broom, D. (1986). Indicators of poor welfare. British Veterinary Journal, 142, 524-526.

Douglas, C., Bateson, M., Walsh, C., Bédué, A., & Edwards, S. (2012). Environmental enrichment induces optimistic cognitive biases pigs. Applied Animal Behaviour Science, 139, 65–73.

Fraser, D., & Duncan, I. (1998). Pleasures, “pains” and animal welfare: Towards a natural history of affect. Animal Welfare. 7, 383–396.

Grandjean, D., & Scherer, K. (2008). Unpacking the cognitive architecture of emotion processes. Emotion. 8, 341–351.

Hallion, L., & Ruscio, A. (2011). A meta-analysis of the effect of cognitive bias modification on anxiety and depression. Psychological Bulletin. 137, 940.

Mendl, M., Burman, O., Parker, R., & Paul, E. (2009). Cognitive bias as an indicator of animal emotion and welfare: emerging evidence and underlying mechanisms. Applied Animal Behavior Science. 118, 161-181.